Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Discovering Relevant Scientific Literature on the Web
IEEE Intelligent Systems
Collaborative Filtering Using Weighted Majority Prediction Algorithms
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Learning Collaborative Information Filters
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Dependency Networks for Collaborative Filtering and Data Visualization
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
An Efficient Boosting Algorithm for Combining Preferences
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Journal of Artificial Intelligence Research
Latent class models for collaborative filtering
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Collaborative filtering based on an iterative prediction method to alleviate the sparsity problem
Proceedings of the 11th International Conference on Information Integration and Web-based Applications & Services
Analyzing category correlations for recommendation system
Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication
Users' (Dis)satisfaction with the personalTV application: Combining objective and subjective data
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
Matrix co-factorization for recommendation with rich side information and implicit feedback
Proceedings of the 2nd International Workshop on Information Heterogeneity and Fusion in Recommender Systems
Information Sciences: an International Journal
Social and behavioural media access
SBNMA '11 Proceedings of the 2011 ACM workshop on Social and behavioural networked media access
Top-N news recommendations in digital newspapers
Knowledge-Based Systems
Alleviating the sparsity problem of collaborative filtering using trust inferences
iTrust'05 Proceedings of the Third international conference on Trust Management
A movie recommendation algorithm based on genre correlations
Expert Systems with Applications: An International Journal
FQAS'06 Proceedings of the 7th international conference on Flexible Query Answering Systems
Opinion leader based filtering
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
A recommendation system based on a subset of raters
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Collaborative Filtering Recommender Systems
Foundations and Trends in Human-Computer Interaction
Neural expert networks for faster combined collaborative and content-based recommendation
Journal of Computational Methods in Sciences and Engineering
Exploring social influence for recommendation: a generative model approach
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Dual role model for question recommendation in community question answering
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Automatic news recommendations via aggregated profiling
Multimedia Tools and Applications
Knowledge-Based Systems
LCARS: a location-content-aware recommender system
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
A Random Walk Model for Item Recommendation in Social Tagging Systems
ACM Transactions on Management Information Systems (TMIS)
Proceedings of the 2013 International Symposium on Wearable Computers
Facing the cold start problem in recommender systems
Expert Systems with Applications: An International Journal
A quality based recommender system to disseminate information in a university digital library
Information Sciences: an International Journal
Statistical user model supported by R-Tree structure
Applied Intelligence
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Recommender systems leverage product and community information to target products to consumers. Researchers have developed collaborative recommenders, content-based recommenders, and a few hybrid systems. We propose a unified probabilistic framework for merging collaborative and content-based recommendations. We extend Hofmarm's (1999) aspect model to incorporate three-way co-occurrence data among users, items, and item content. The relative influence of collaboration data versus content data is not imposed as an exogenous parameter, but rather emerges naturally from the given data sources. However, global probabilistic models coupled with standard EM learning algorithms tend to drastically overfit in the sparsedata situations typical of recommendation applications. We show that secondary content information can often be used to overcome sparsity. Experiments on data from the Researchlndex library of Computer Science publications show that appropriate mixture models incorporating secondary data produce significantly better quality recommenders than k-nearest neighbors (k-NN). Global probabilistic models also allow more general inferences than local methods like k-NN.